EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices

Real-time video analytics on edge devices for changing scenes remains a difficult task. As edge devices are usually resource-constrained, edge deep neural networks (DNNs) have fewer weights and shallower architectures than general DNNs.

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Cite this as

Liang Wang, Nan Zhang, Xiaoyang Qu, Jianzong Wang, Jiguang Wan, Guokuan Li, Kaiyu Hu, Guilin Jiang, Jing Xiao (2024). Dataset: EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices. https://doi.org/10.57702/nfqlu5a5

DOI retrieved: December 16, 2024

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2308.08717
Author Liang Wang
More Authors
Nan Zhang
Xiaoyang Qu
Jianzong Wang
Jiguang Wan
Guokuan Li
Kaiyu Hu
Guilin Jiang
Jing Xiao